WO2012022170A1 - 频谱感知方法、装置及系统 - Google Patents

频谱感知方法、装置及系统 Download PDF

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Publication number
WO2012022170A1
WO2012022170A1 PCT/CN2011/073640 CN2011073640W WO2012022170A1 WO 2012022170 A1 WO2012022170 A1 WO 2012022170A1 CN 2011073640 W CN2011073640 W CN 2011073640W WO 2012022170 A1 WO2012022170 A1 WO 2012022170A1
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Prior art keywords
sensing
target
channel
channels
node
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PCT/CN2011/073640
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English (en)
French (fr)
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邱晶
张黔
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华为技术有限公司
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Publication of WO2012022170A1 publication Critical patent/WO2012022170A1/zh
Priority to US13/768,006 priority Critical patent/US20130157580A1/en

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/14—Spectrum sharing arrangements between different networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/02—Traffic management, e.g. flow control or congestion control
    • H04W28/06—Optimizing the usage of the radio link, e.g. header compression, information sizing, discarding information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management

Definitions

  • Embodiments of the present invention relate to wireless communication technologies, and in particular, to a technique for sensing radio. Background technique
  • a cognitive radio is a radio system in which a secondary user (unauthorized user) communicates over a multidimensional use of idle spectrum resources, such as space, frequency, and time, without causing interference to the primary user (authorized user).
  • idle frequency detection technology is one of the key technologies to determine whether the cognitive radio technology can be realized. Therefore, spectrum sensing becomes an important technology for cognitive radio.
  • the purpose of spectrum sensing is to monitor and detect the activity of the primary user signal on a particular frequency band.
  • the cognitive radio system can use the spectrum; and when the primary user signal is detected, the cognitive radio system must The band was launched at the specified time.
  • the spectrum sensing and data transmission of the spectrum sensing of the secondary user cannot be performed simultaneously.
  • the sensing time needs to be as long as possible, and the corresponding sub-user data transmission time is reduced, so that the throughput is reduced. If the sensing time is reduced, the sub-user data transmission conflicts with the main user. , also caused a reduction in throughput.
  • most of the target channels are spectrum-aware. Therefore, how to reduce the perceived time and improve the throughput under the condition of satisfying the perceptual accuracy requirements becomes an important issue in the field of cognitive radio. Summary of the invention
  • Embodiments of the present invention provide a method for performing spectrum sensing by using inter-channel correlation, which can reduce the sensing time and improve throughput under the condition of satisfying the perceptual accuracy requirement.
  • the embodiment of the invention provides a spectrum sensing method, including:
  • the embodiment of the present invention further provides a spectrum sensing node, including:
  • a measurement fusion module configured to obtain correlation information between target channels
  • a spectrum sensing module configured to obtain spectrum sensing results of at least one of the target channels;
  • a measurement and analysis module configured to determine, according to spectrum sensing results of the at least one target channel and correlation information between the target channels, other target channels Perceive the results.
  • An embodiment of the present invention further provides a frequency awareness system, including:
  • a sensing node configured to obtain correlation information between target channels from the measurement and fusion node, perform channel sensing on at least one target channel, and predict states of other unperceived channels according to the sensing result and channel correlation information, and determine other The perceived result of the target channel.
  • FIG. 1 is a flow chart showing a method according to an embodiment of the present invention
  • FIG. 2 is a schematic diagram showing a slot configuration according to an embodiment of the present invention.
  • FIG. 3 is a diagram showing a spectrum sensing system based on spectrum prediction according to an embodiment of the present invention
  • FIG. 4 is a block diagram showing the structure of a node of a dynamic frequency access system based on frequency prediction in the present embodiment.
  • DETAILED DESCRIPTION In the prior art, a secondary user needs to perceive each target spectrum to determine whether the target spectrum is in an idle state.
  • the embodiment of the present invention provides a spectrum sensing system based on frequency prediction, which predicts the sensing results of other spectrums according to partial sensing results through correlation between channels.
  • the sensing fusion node and the sensing node may be included.
  • the function of sensing measurement fusion may also be placed on a sensing node.
  • Correlation information between target channels is used to characterize the similarity of spectrum usage between channels.
  • the channel state of the next time slot of each channel has a strong correlation with the historical state of the channel. Therefore, it is possible to perform spectrum sensing on some channels, and use the obtained channel correlation information to predict the state of other unperceived channels.
  • S102 Obtain a spectrum sensing result of at least one of the target channels.
  • the sensing measurement fusion node is included in the system, the correlation information between the target channels is calculated by the sensing measurement fusion node, and the sensing node senses, and the sensing result is sent to the sensing measurement fusion node.
  • a specific sensing node called a central sensing node, calculates and obtains correlation information between target channels, and the center sensing node perceives part of the target channel to directly obtain spectrum sensing results of the target channel.
  • the state of the other unperceived channels can be predicted based on the perceived result and the correlation between the channels.
  • a correlation threshold may be set. If the correlation between the two channels is greater than the threshold, if the sensing result of the first channel is perceived, the second channel is predicted to be the first by prediction. The channel has the same perceived result, so that the second channel is not actually perceived, but the correlation between the two channels is used for prediction.
  • the channel that is not actually perceived may be determined based on the perceived result of the channel whose similarity is greater than the threshold. Therefore, the actual perceived channel is at least one, and may be multiple. Therefore, determining the perceived result of the other target channel may be that when the similarity of the other channel to the at least one target channel is greater than a threshold, the perceived result of the other target channel is the same as the perceived result of the at least one target channel.
  • the inter-channel correlation prediction is used to obtain other un-sensing new sensing results, which reduces the spectrum sensing overhead and improves the system throughput.
  • the spectrum measurement result may be a dynamic input of other spectrum measurement nodes, or a pre-acquired static history frequency measurement information.
  • the correlation information between the target channels may include: a probability of the number of occurrences and occurrence times of the primary users on the two channels; or a traffic similarity on the two channels; or a similarity of the signal to interference and noise ratios on the two channels, and the like.
  • correlation information between channels is used to characterize the similarity of spectrum usage between channels.
  • the probability of occurrence and the probability of occurrence time are used to characterize the correlation information between channels, that is, the probability of occurrence and the probability of occurrence as measurement information, which can be understood as the main Whether the user has appeared on channel c.
  • the historical measurement information of channel c can be expressed as a sequence of states, such as idle information of the channel,
  • CSI(c) ⁇ CSI(c, t, ), CSI(c, t 2 ),...CSI(c, t n ) ⁇
  • CSI is channel state information
  • the sensing node performs channel sensing on a part of the target channel to obtain a sensing result of the partial target channel.
  • a perceptual time slot configuration manner of the sensing node is as shown in FIG. 2.
  • a complete sensing period is composed of at least one sensing period and a data transmission period.
  • multiple channel sensing is performed. .
  • the number and order of perceived channels during the sensing period depends on the spectrum sensing strategy.
  • the spectrum sensing strategy can be determined according to the correlation between channels.
  • the sensing node or the measuring fusion node determines each perceived channel (i.e., which channel is perceived) according to the sensing policy.
  • the sensing node performs channel sensing to obtain the perceptual result.
  • the sensing policy may be first determined, the sensing order of the selected target channel is determined, and the selected target channel is perceived according to the sensing order.
  • the sensing strategy is determined based on the specific target of the sensing node, and may be based on a specific optimization target and constraints.
  • the optimization objectives may include: maximizing the average throughput of a single node, or maximizing the average throughput of the system, and the constraints may include: a probability of collision with the primary user, a maximum access capability of the secondary user, and the like.
  • the sensing order of the target channel is determined according to the collision probability of the secondary user and the primary user or the maximum access capability of the secondary user, and the sensing sequence maximizes the average throughput of the single node as much as possible, or maximizes the average throughput of the system. In practice, it may be close to the maximum.
  • the following example illustrates a spectrum sensing strategy based on single node average throughput maximization.
  • R(CA V) CA V(n)B(T - it) IT (2)
  • N the set of perceived channels
  • B the bandwidth of a single channel
  • T a perceptual period
  • t the time to perceive a channel
  • Equation (2) indicates the average throughput of a single node after access is perceived for i channels.
  • the set N of perceived channels refers to the channel that actually needs to be perceived, and does not include the channel that determines the perceived result by prediction. All of the target channels include the target channel that actually performs the sensing and the channel that obtains the perceived result by the prediction.
  • Ri AV, a) E[R ⁇ CA V Next ) - R(CA V Curre ) (3)
  • the optimization goal of the node can be defined as the maximum increase in the average throughput per perception period, ie:
  • the best spectrum sensing strategy for the sensing node is the optimal channel sensing order that satisfies (4).
  • spectrum sensing can be implemented by a single node or by multiple nodes. If single-point sensing is used, single-node sensing sensitivity may be limited, and single-node sensing can only reflect the spectrum availability around the node, but not the spectrum availability of the entire communication range. If multi-node cooperative spectrum sensing can solve these two problems, cooperative spectrum sensing utilizes the spatial diversity formed by the sensing nodes of different geographical locations in the CR network, which greatly improves the global detection performance and can obtain the global spectrum availability. . If the multi-point aware mode is used, the sensing node can be sent to the sensing measurement fusion node or the central sensing node. There is inter-channel correlation information on the perceptual measurement fusion node or the central sensing node.
  • S203 Determine, according to the sensing result of the partial target channel and the correlation information between the target channels, other spectrum sensing results for performing the actual sensing channel.
  • the availability of the channel (CA, Channel Availability) is used to indicate the probability that the channel is idle at a certain moment.
  • the availability of this channel can be determined based on the probability of the number of occurrences and time of occurrence of the primary user on the channel, or the traffic situation of the primary user or the signal drying ratio of the channel. When the number of times the primary user appears, the shorter the time, the higher the availability, the less the primary user's service, the higher the availability, or the greater the channel's letter drying ratio, the greater the availability.
  • CAV Channel Availability Vector
  • the channel correlation can be dynamically updated according to the perceptual result, thus implying the time variation dimension.
  • the correlation between the calculated channels may be the sensing node to the perceptual measurement fusion node or the central sensing node. Therefore, the whole method can have two implementation modes. One is that the perceptual measurement fusion node calculates and stores inter-channel correlation information, which receives or acquires the perceptual result of other sensing nodes on part of the target channel, and then according to the perceptual result of the partial target channel. The correlation with the target channel determines the spectral sensing results of the other channels.
  • the function of the sensing node is placed on the center sensing node, and the center sensing node calculates and stores the inter-channel correlation information, and then the node performs the perceptual activity sensing result on the selected part of the target channel, if multiple points are used. Perceptually, it receives or acquires the perceptual result of the selected target channel by other sensing nodes, and then determines the spectrum sensing result of the other channel according to the sensing result of the partial target channel and the correlation between the target channels.
  • ETP ⁇ c -CA V ⁇ c) log 2 (CA V(c)) - ⁇ - CA V ⁇ c)) log 2 (1 - CA V ⁇ c))
  • the prediction result of the channel is updated by the low uncertainty update criterion, and the low uncertainty update criterion can be described as: when the channel c is predicted by using (5), if the predicted channel state entropy is smaller than The channel state entropy before prediction updates the current state of channel c according to the prediction result of equation (5).
  • the time of the sensing period is reduced, and the correlation between the channels is used to obtain other un-sensing new sensing results, thereby reducing the spectrum sensing overhead and improving the system.
  • Throughput the correlation between channels is used to determine the order and strategy of the target channel that needs to be perceived, and the other target channel activity perception results are predicted based on the perceived result.
  • the accuracy of the system is increased, and the sensing time can be further improved to reduce the sensing time and improve the throughput.
  • the information of the binding relationship may exist on the sensing node or in the measurement of the fusion node or other nodes of the system.
  • the sensing node can obtain the binding relationship during the sensing process of the target channel, that is, obtain correlation information between the target channels.
  • the sensing nodes perceive one by one, they first look up the binding relationship and firstly perceive some of the target channels involved in the binding relationship. If there is a binding relationship and the existing spectrum is perceived to be completed, the other target channels do not need to be perceived but are bound. Relationship prediction is determined.
  • the embodiment of the present invention further provides a system for implementing the foregoing method, including measuring a fusion node and a sensing node, where the measurement fusion node and the sensing node may be located at a node such as a gateway, a base station, a relay station, and a terminal.
  • a node such as a gateway, a base station, a relay station, and a terminal.
  • the following uses the cooperative spectrum sensing involved in the base station and the mobile terminal in the cellular network as an example to illustrate the application of the above method.
  • the base station performs unified management on terminals participating in the cooperative spectrum in the cell, including sensing node selection, sensing task allocation, and sensing and access policy decisions.
  • the base station sends the decision result of the spectrum sensing policy to all the terminals participating in the cooperative spectrum sensing.
  • the terminal performs local sensing, and reports the sensing result to the base station.
  • the base station aggregates the sensing results of all the cooperative sensing nodes, and
  • a frequency perception based spectrum sensing system 30 is shown in FIG.
  • System 30 includes a spectrum measurement fusion node 301 and at least one sensing node 302. In a particular system, there may be multiple sensing nodes 302.
  • the measurement fusion node 301 can obtain the correlation between the target channels. First, the correlation between the target channels is calculated based on the existing spectrum measurement results.
  • the existing spectrum measurement results may be dynamic inputs of other spectrum measurement nodes, or static historical spectrum measurement information obtained in advance.
  • Correlation between target channels Information is used to characterize the similarity of inter-channel frequency usage. The probability of the number of occurrences and time of occurrence of the primary user on the two channels; or the similarity of the traffic on the two channels; or the similarity of the signal to interference and noise ratios on the two channels.
  • the sensing node 302 obtains the correlation between the target channels from the measurement fusion node 301, and the sensing node 302 performs channel sensing on at least one target channel, and predicts the state of other unperceived channels according to the sensing result and the channel correlation information, and determines other targets.
  • the perceived result of the channel The sensing node 302 determines that the perceived result of the other target channel is the same as the perceived result of the at least one target channel when the similarity of the other channel to the at least one target channel is greater than a threshold.
  • the measurement fusion node 301 determines the sensing policy according to the correlation between the target channels, selects the target channel that needs to be perceived by the sensing node 302, and determines the sensing order. It is also possible to obtain the correlation between the target channels by the sensing node 302, determine the sensing policy of the sensing node, select a target channel that needs to be perceived by the sensing node, and determine the sensing order. Whether the measurement fusion node 301 or the sensing node 302 determines the sensing order of the target channel according to the collision probability of the secondary user and the primary user or the maximum access capability of the secondary user, the sensing order maximizes the average throughput of the single node, or the system The average throughput is maximized.
  • the sensing node 302 can also calculate the entropy of the target channel obtained by predicting the perceived result, use entropy to indicate the degree of uncertainty of the channel, and then correct the sensing result of the other target channel according to the low uncertainty criterion.
  • FIG. 4 is a structural block diagram of a node of a dynamic frequency access system based on frequency prediction in the present embodiment.
  • the node 400 includes: a measurement fusion module 402, a spectrum sensing module 404, and a measurement analysis module 406.
  • the measurement fusion module 402 is configured to obtain correlation information between target channels.
  • Correlation information between target channels is used to characterize
  • the degree of similarity of inter-channel frequency usage may be the probability of the number of occurrences and appearance times of the primary users on the two channels, or the similarity of the traffic on the two channels, or the similarity of the signal to interference and noise ratios on the two channels.
  • the spectrum sensing module 404 is configured to obtain a spectrum sensing result of at least one of the target channels.
  • the spectrum sensing module 404 obtains the spectrum sensing result of the target channel in two ways. One can obtain a perceptual result for the node to perceive the target channel. The second is to receive the other channel to perceive the target channel.
  • the current node can be considered as a measurement fusion node or a center-aware node. After the sensing node completes the sensing of the target channel, the result is notified to the current node.
  • the measurement analyzing module 406 is configured to determine the sensing result of the other target channel according to the learned spectrum sensing result of the at least one target channel and the correlation information between the target channels. The measurement analysis module 406 determines that the perceived result of the other target channel is the same as the perceived result of the at least one target channel when the similarity of the other channel to the at least one target channel is greater than a threshold.
  • the time of the sensing period is reduced, and the correlation between the channels is used to obtain other un-sensing new sensing results, thereby reducing the spectrum sensing overhead and improving the system.
  • Throughput In the embodiment of the present invention, only part of the channel needs to be spectrum-aware, the time of the sensing period is reduced, and the correlation between the channels is used to obtain other un-sensing new sensing results, thereby reducing the spectrum sensing overhead and improving the system. Throughput.
  • the node 400 further includes a spectrum sensing decision module 408, configured to determine a sensing policy, select at least one target channel in the target channel according to correlation information between the target channels, perform spectrum sensing, and determine the selected target.
  • the perceptual order of the channels, the selected target channels are perceived in the perceptual order.
  • the spectrum sensing module 404 is based on the sensing policy determined by the spectrum sensing decision module 408.
  • the current node may also send the sensing policy determined by the frequency-subsequent sensing decision module 408 to other sensing nodes, and the other sensing nodes perceive the target channel according to the sensing policy, and then send the sensing result to the current node.
  • the spectrum sensing module 404 can directly directly target the target At least one target channel in the track performs spectrum sensing; or the other at least one target channel spectrum sensing result sent by the sensing node is sent to the spectrum sensing module 404, wherein the other sensing node performs spectrum sensing on the target channel.
  • the spectrum sensing decision module 408 determines the sensing order of the target channel according to the collision probability of the secondary user and the primary user or the maximum access capability of the secondary user, and the sensing order maximizes the average throughput of the single node as much as possible, or maximizes the average throughput of the system.
  • a correction module 410 is further included in the node 400, and the correction module 410 calculates an entropy of the target channel obtained by predicting the perceived result, and uses entropy to indicate the degree of uncertainty of the channel, and then according to the low uncertainty criterion The perceived results of other target channels are corrected.
  • the time of the sensing period is reduced, and the correlation between the channels is used to obtain other un-sensing new sensing results, thereby reducing the spectrum sensing overhead and improving the system.
  • Throughput the correlation between channels is used to determine the order and strategy of the target channel to be perceived, and the other target channel activity sensing results are predicted according to the perceived result, the accuracy of the system is improved, and the sensing accuracy can be further satisfied, and the sensing is reduced. Time increases throughput.
  • the foregoing program may be stored in a computer readable storage medium, and the program is executed when executed.
  • the foregoing steps include the steps of the foregoing method embodiments; and the foregoing storage medium includes: a medium that can store program codes, such as a ROM, a RAM, a magnetic disk, or an optical disk.

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Description

频讲感知方法、 装置及系统
技术领域
本发明实施例涉及无线通信技术， 特别是涉及一种感知无线电的技术。 背景技术
随着无线通信业务需求的高速增长， 目前可用的频谱资源正在变得越来越 稀缺， 由此出现了感知无线电 （Cognitive Radio, CR )。 感知无线电是一种无 线电系统， 次用户 （非授权用户）在不对主用户 （授权用户）造成干扰的情况 下从空间、频率及时间等多维的利用空闲频谱资源进行通信。在感知无线电系 统中， 空闲频语检测技术是决定感知无线电技术能否实现的关键技术之一。 因 此频谱感知成为感知无线电一项重要技术。
频谱感知的目的是监视和检测特定频段上的主用户信号的活动情况， 当 检测到空闲频语存在时，感知无线电系统可以使用该频谱； 而当检测到主用户 信号出现时，感知无线电系统必须在规定的时间推出该频段。 为了能够对主用 户信号进行有效的检测，要求次用户的频谱感知的频谱感知和数据传输不能同 时进行。 为了增加感知准确度， 需要尽可能长的感知时间， 相应的次用户数据 传输的时间则减少， 使得吞吐量降低； 而如果减小感知时间， 则会造成次用户 的数据传输与主用户产生冲突， 同样造成吞吐量的降低。 目前的做法大多对每 一条目标信道进行频谱感知， 因此， 如何在满足感知精度要求的条件下， 减少 感知时间提高吞吐量成为感知无线电领域的重要问题。 发明内容
本发明实施例提供一种利用信道间相关性进行频谱感知的方法，实现在满 足感知精度要求的条件下， 减少感知时间提高吞吐量。
本发明实施例给出一种频谱感知方法， 包括：
获得目标信道间的相关性信息；
获得至少一条所述目标信道的频谱感知结果；
根据所述至少一条目标信道的频谱感知结果及所述目标信道间的相关性 信息确定其他目标信道的感知结果。
进一步， 本发明实施例还提供一种频谱感知节点， 包括：
测量融合模块， 用于获得目标信道间的相关性信息；
谱感知模块， 用于获得至少一条所述目标信道的频谱感知结果； 测量分析模块，用于根据所述至少一条目标信道的频谱感知结果及所述目 标信道间的相关性信息确定其他目标信道的感知结果。
本发明实施例还给出一种频语感知系统， 包括：
测量融合节点， 用于获得目标信道间的相关性；
感知节点， 用于从所述测量融合节点获得目标信道间的相关性信息，对至 少一条目标信道进行信道感知， 并根据感知结果和信道的相关性信息，预测其 它未感知信道的状态， 确定其他目标信道的感知结果。
本发明实施例， 只需要对部分信道进行频谱感知， 减少了感知期的时间， 利用信道间的相关性预测获得其他未感知新到的感知结果，这样降低了频谱感 知的开销， 提高了系统的吞吐量。 附图说明
图 1所示为所示为本发明实施例的方法流程图；
图 2所示为本发明施实例 知时隙配置图；
图 3所示为本发明施实例一种基于频谱预测的频谱感知系统图；
图 4所示为本实施例中基于频普预测的动态频语接入系统节点结构框图。 具体实施方式 在现有技术中次用户需要对每一个目标频谱进行感知确定目标频谱是否 处于空闲状态。本发明实施例给出一种基于频语预测的频谱感知系统，通过信 道间的相关性根据部分感知结果预测其他频谱的感知结果。
在一个基于频 "普预测的动态接入系统中，可以包括感知测量融合节点及感 知节点。 实践中， 可以也可以将感知测量融合的功能放置在一个感知节点上。 如图 1所示为本发明实施例的方法流程图。
5101 , 获得目标信道间的相关性信息。
目标信道间的相关性信息用来表征信道间频谱使用情况的相似程度。在本 发明实施例的研究中发现，每个信道下一时隙的信道状态与该信道的历史状态 有较强的相关性。 因此可以对部分信道进行频谱感知的基石出上， 利用获得的信 道相关性信息预测其他未感知的信道的状态。
5102, 获得至少一条所述目标信道的频谱感知结果。
对部分目标信道进行频谱感知，这里的部分信道可以是至少一条待进行频 谱感知的目标信道。
如果在系统中包括有感知测量融合节点则在感知测量融合节点计算目标 信道间的相关性信息， 由感知节点进行感知，将感知结果发送给感知测量融合 节点。 另一种实现可以为， 某一特定的感知节点， 称为中心感知节点， 其计算 获得目标信道间的相关性信息， 该中心感知节点对部分目标信道进行感知， 直 接获得目标信道的频谱感知结果。
S103 ,根据所述至少一条目标信道的频谱感知结果及所述目标信道间的相 关性信息确定其他目标信道的感知结果。
由于信道间具有相关性，在对部分信道进行感知后，根据感知的结果和信 道间的相关性， 可以预测获得其他未感知的信道的状态。
作为一种实现方式， 可以设定一个相关性阈值， 如果两条信道间的相关性 大于该阈值，如果感知到其中第一条信道的感知结果， 则第二条信道通过预测 认为与第一条信道有同样的感知结果，从而不用实际感知第二条信道而是通过 两条信道间的相关性进行预测确定。 而未进行实际感知的信道，都可以根据与 其相似性大于阈值的信道的感知结果预测确定。所以进行实际感知的信道至少 为一条， 可能为多条。 因此确定其他目标信道的感知结果可以为当其他信道与 所述至少一条目标信道的相似性大于一阈值时，所述其他目标信道的感知结果 与所述至少一条目标信道的感知结果相同。
例如， 我们认为信道相关性大于 95%时， 两条信道有同样的感知结果。 在 某一时刻， 感知到信道 c的状态为空闲， 由于信道 d与信道 c的信道相关性为 96%, 则认为此刻信道 d的状态也为空闲。
本发明实施例， 只需要对部分信道进行频谱感知， 减少了感知期的时间， 利用信道间的相关性预测获得其他未感知新到的感知结果，这样降低了频谱感 知的开销， 提高了系统的吞吐量。
进一步， 本发明频语预测的又一方法实施例。
S201 , 根据频谱测量结果， 计算信道之间的相关性。
频谱测量结果可以是其它频谱测量节点的动态输入，或预先获得的静态历 史频语测量信息。 目标信道间的相关性信息可以包括： 两个信道上主用户出现 次数和出现时间的概率； 或两个信道上业务相似度； 或两个信道上的信干噪比 的相似度等。 总之，信道间的相关性信息用来表征信道间频谱使用情况的相似 程度。
下面举例说明信道相关性的一种计算方法，在本例中用出现次数和出现时 间的概率表征信道间的相关性信息，即出现次数和出现时间的概率作为测量信 息， 具体可以理解为指主用户在信道 c上是否出现过。 信道 c的历史测量信息可以表示为一个状态序列， 例如信道的空闲信息,
CSI(c) = {CSI(c, t, ), CSI(c, t2 ),...CSI(c, tn )}
即信道上主用户出现的次数和时间情况：
其中， t为不同时隙 CSI为信道状态信息，
信道 c 1和 c2之间的相关性 ， c2 )可以表示为，
JO,如果信道 c在时隙 t是空闲的
(C' ° = l,如果信道 c在时隙 t是繁忙的
ρ(ολ , ο2 ) = ^- (1)
A + D ^ = (^( 1 ) @ ^( 2))中0的个数， 表示两个序列中相同元素的个数
D = (CSi{cx ) ® CSI(c2 ))中1的个数， 表示两个序列中不同元素的个数
S202,感知节点对部分目标信道进行信道感知获得部分目标信道的感知结 果。
在本实施例中， 感知节点的一种感知时隙配置方式如图 2所示，一个完整 的感知周期由至少一个感知期和数据传输期组成.在一个感知期内， 进行多个 信道的感知。感知期内被感知信道的数量以及顺序取决于频谱感知策略。在本 实施例中， 可以根据信道间的相关性才决定频谱感知策略。 首先感知节点或者 是测量融合节点根据感知策略确定每次感知的信道 (即感知哪个信道）。 感知 节点进行信道感知获得感知结果。
实践中，可以先确定感知策略，确定对所述选择出的目标信道的感知顺序， 按所述感知顺序对所述选择出的目标信道进行感知。感知节点对部分目标信道 进行信道感知获得部分目标信道的感知结果时，感知策略的确定基于感知节点 的特定目标， 可基于特定的优化目标以及约束条件。 优化目标可以包括： 单节 点平均吞吐量最大化， 或系统平均吞吐量最大化等， 约束条件可以包括： 与主 用户的冲突概率、次用户的最大接入能力等。 比如根据次用户与主用户的冲突 概率或次用户的最大接入能力确定所述目标信道的感知顺序，所述感知顺序尽 量使单节点平均吞吐量最大化， 或系统平均吞吐量最大化。 实践中可能是接近 最大即可。
下面举例说明一种基于单节点平均吞吐量最大化的频谱感知策略。
用 R ( CAV )表示感知节点平均吞吐量， R(CA V) = CA V(n)B(T - it) I T (2) 其中， N为被感知信道的集合， B是单个信道带宽， T是一个感知周期， t 是感知一个信道的时间。 （2 )式表示感知了 i个信道后进行接入， 单节点的平 均吞吐量。 被感知信道的集合 N, 是指实际需要感知的信道， 不包括通过预测 确定感知结果的信道。全部的目标信道包括实际进行感知的目标信道和通过预 测的获得感知结果的信道。
下一次釆取感知行为， 感知信道 a后， 节点获得的吞吐量增益为
ri A V, a) = E[R{CA VNext) - R(CA VCurre ] (3) 节点的优化目标可以定义为每个感知周期内的平均吞吐量增量最大化， 即：
Figure imgf000009_0001
感知节点的最佳频谱感知策略 是指满足（4 ) 式的最佳信道感知顺序。 在确定感知顺序后， 频谱感知可以通过单个节点实现，也可以通过多个节 点协作实现。 如果釆用单点感知， 则可能单节点感知灵敏度有限， 并且单节点 感知只能反映本节点周围的频谱可用情况，而不能反映整个通信范围的频谱可 用情况。如果釆用多节点协同频谱感知可以解决这两个方面的问题，协同频谱 感知利用 CR网络内不同地理位置的感知节点构成的空间分集， 大大提高了全 局检测性能， 并且可以获得全局的频谱可用情况。 如果釆用多点感知的模式， 则可以将感知节点给感知测量融合节点或者中心感知节点。在感知测量融合节 点或者中心感知节点上有信道间相关性信息。
S203 ,才艮据对部分目标信道的感知结果和目标信道间的相关性信息预测确 定其他为进行实际感知信道的频谱感知结果。 利用信道的可用度（CA, Channel Availability )表示信道在某个时刻空闲 的概率。 这个信道的可用度可以根据信道上主用户出现次数和出现时间的概 率， 或者主用户的业务情况或者该信道的信干燥比确定。 当主用户出现时间次 数越少出现时间越短则其可用度越高， 主用户的业务越少则其可用度也越高， 或者信道的信干燥比越大其可用度越大。
信道 c的可用度表示为：
CA(c,t) = P{CSI(c,t) = 0}
CAV ( Channel Availability Vector )表示一组信道的可用度。
CAV(c,t) = CA(c,t) = P{CSI(c,t) = 0} il if CSI(c,t) = 0
CAV(c,t)
[0 if CSI(fi,t、 = \ 当对信道 S进行感知后， 其它未感知信道 C的可用度可以通过下式获得:
P{CSI(c, t) = CSI(s,t)} if CSI(s, t) = 0
CAV(c,t) =
P {CSI(c, t)≠ CSI(s,t ) if CSI(s, t) = 1
根据统计理论， 当信道的历史测量信息足够多时,
Figure imgf000010_0001
根据 (1)式,
Figure imgf000010_0002
上式 (5)中， 信道相关性 可根据感知结果进行动态更新， 因此隐含了时间 的变化维度。 在上述的实施例中，计算信道之间的相关性可以是感知节点给感知测量融 合节点或者中心感知节点。 因此整个方法可以有两种实施模式， 一是感知测量 融合节点计算并存有信道间相关性信息，其接收或获取其他感知节点对部分目 标信道的感知结果，然后再根据对部分目标信道的感知结果和目标信道间的相 关性确定其他信道的频谱感知结果。 另一种模式，感知测量节点的功能放置在 中心感知节点上， 中心感知节点计算并存有信道间相关性信息， 然后该节点对 选择出的部分目标信道进行感知活动感知结果，如果釆用多点感知， 其接收或 者获取其他感知节点对选择出的部分目标信道的感知结果，然后再根据对部分 目标信道的感知结果和目标信道间的相关性确定其他信道的频谱感知结果。
进一步， 釆用信道预测方法， 可能会出现两个不同信道 (sl,s2)的感知结果 对同一个信道 (c)产生不同的预测。 因此，需要进一步增加其他目标信道的感知 结果的更新准则。 用 ETP表示信道状态的熵， 用信道的熵来表示信道的不确定 程度， 则对于信道 c其 ETP的计算如下：
ETP{c) = -CA V{c) log2 (CA V(c)) - {\ - CA V{c)) log2 (1 - CA V{c))
熵越小说明信道的不确定性越小， 即更容易判断信道当前的状态（0或 1 )。 本 实施例通过低不确定性更新准则更新对信道的预测感知结果，低不确定性更新 准则可以描述为： 当釆用 （5 )式对信道 c进行预测时， 若预测后的信道状态熵 小于预测前的信道状态熵， 则按照 （5 ) 式的预测结果更新信道 c的当前状态。
本发明实施例， 只需要对部分信道进行频谱感知， 减少了感知期的时间， 利用信道间的相关性预测获得其他未感知新到的感知结果，这样降低了频谱感 知的开销，提高了系统的吞吐量。 同时利用信道间的相关性来确定需要感知的 目标信道的顺序及策略，根据感知的结果预测其他目标信道活动感知结果，提 高了系统的准确性， 能够进一步满足感知精度要求的条件下， 减少感知时间提 高吞吐量。
从上述方法实施的角度，给出又一个实施例。先确定目标频谱直接的相关 性，把确定有相关性的频谱组成绑定关系。绑定关系的信息可以存在感知节点 上，也可在测量融合节点或者系统其他的节点。感知节点在进行目标信道的感 知过程中， 可以获得该绑定关系， 即获得目标信道间的相关性信息。 感知节点 逐个进行感知之前，先查找绑定关系，先感知绑定关系中涉及的部分目标信道， 如果存在绑定关系并且已有频谱已感知完成，那么其他目标信道不需要感知而 是 居绑定关系预测确定。
本发明实施例进一步提供实现上述方法的系统，包括测量融合节点及感知 节点， 上述测量融合节点及感知节点可以位于网关、基站、 中继站以及终端等 节点。 下面以蜂窝网络中基站和移动终端参与的合作频谱感知为例，说明上述 方法的应用。在蜂窝网络的合作频谱感知中， 由基站对小区内参与协作频谱感 知的终端进行统一管理， 包括感知节点选择、感知任务分配以及感知和接入策 略决策等。基站将频谱感知策略的决策结果下发给所有参与协作频谱感知的终 端， 终端进行本地感知， 将感知结果上报基站， 由基站对所有协作感知节点的 感知结果进行融合， 并基于信道的相关性信息进行感知和接入决策。
如图 3所示的一种基于频语预测的频谱感知系统 30。 系统 30包括频谱测量 融合节点 301及至少一个感知节点 302,在具体的系统中， 可以有多个感知节点 302。 测量融合节点 301可以获得目标信道间的相关性。 首先根据已有的频谱测 量结果，计算目标信道间的相关性。 已有的频谱测量结果可以是其它频谱测量 节点的动态输入， 或事先获得的静态历史频谱测量信息。 目标信道间的相关性 信息用来表征信道间频语使用情况的相似程度。可以为两个信道上主用户出现 次数和出现时间的概率； 或两个信道上业务相似度； 或两个信道上的信干噪比 的相似度。感知节点 302从测量融合节点 301获得目标信道间的相关性，感知节 点 302对至少一条目标信道进行信道感知， 并根据感知结果和信道的相关性信 息，预测其它未感知信道的状态，确定其他目标信道的感知结果。感知节点 302 在当所述其他信道与所述至少一条目标信道的相似性大于一阈值时，确定所述 其他目标信道的感知结果与所述至少一条目标信道的感知结果相同。
进一步， 测量融合节点 301根据目标信道间的相关性确定感知策略， 选择 出需要感知节点 302进行感知的目标信道， 并确定感知顺序。 也可以由感知节 点 302获得目标信道间的相关性后确定该感知节点的感知策略选择出需要感知 节点进行感知的目标信道， 并确定感知顺序。 无论是测量融合节点 301或者是 感知节点 302其根据次用户与主用户的冲突概率或次用户的最大接入能力确定 目标信道的感知顺序，感知顺序尽量使单节点平均吞吐量最大化， 或系统平均 吞吐量最大化。
进一步，感知节点 302还可以计算通过预测获得感知结果的目标信道的熵， 用熵来表示该信道的不确定程度，再根据低不确定性准则对所述其他目标信道 的感知结果进行修正。
本发明实施例再给出一种基于频语预测的频谱感知系统节点，该节点实现 上述的方法。 这里的节点可以位于网关、 基站、 中继站以及终端等节点。 如图 4所示为本实施例中基于频语预测的动态频语接入系统节点结构框图。节点 400 包括： 测量融合模块 402, 频谱感知模块 404, 测量分析模块 406。 测量融合模 块 402用于获得目标信道间的相关性信息。 目标信道间的相关性信息用来表征 信道间频语使用情况的相似程度，可以是两个信道上主用户出现次数和出现时 间的概率， 或两个信道上业务相似度， 或两个信道上的信干噪比的相似度。 频 谱感知模块 404用于获得至少一条所述目标信道的频谱感知结果。 频谱感知模 块 404获得目标信道的频谱感知结果有两种方式。 其一可以为该节点对目标信 道进行感知获得感知结果。 其二为接收其他信道对目标信道进行感知后的结 果，如果是该种方法在基于预测的于频 "普预测的频谱感知系统中， 当前的节点 可以认为是测量融合节点或中心感知节点。其他感知节点完成对目标信道的感 知后， 将结果通知到当前节点。 测量分析模块 406用于根据已获知的至少一条 目标信道的频谱感知结果及目标信道间的相关性信息确定其他目标信道的感 知结果。 测量分析模块 406在当所述其他信道与所述至少一条目标信道的相似 性大于一阈值时，确定所述其他目标信道的感知结果与所述至少一条目标信道 的感知结果相同。
本发明实施例， 只需要对部分信道进行频谱感知， 减少了感知期的时间， 利用信道间的相关性预测获得其他未感知新到的感知结果，这样降低了频谱感 知的开销， 提高了系统的吞吐量。
进一步， 在节点 400中还包括频谱感知决策模块 408 , 用于确定感知策略， 根据目标信道间的相关性信息在目标信道中选择至少一条目标信道进行频谱 感知， 并确定对所述选择出的目标信道的感知顺序，按所述感知顺序对所述选 择出的目标信道进行感知。 实现中， 频谱感知模块 404根据频谱感知决策模块 408确定的感知策略。还可以当前节点将频 -潜感知决策模块 408确定的感知策略 发送给其他感知节点， 其他感知节点根据感知策略对目标信道进行感知， 并将 感知结果再发送给当前节点。 所以说频谱感知模块 404可以直接对所述目标信 道中的至少一条目标信道进行频谱感知；或其他接收感知节点发送的所述至少 一条目标信道频谱感知结果给频谱感知模块 404, 其中由其他感知节点对目标 信道进行频谱感知。 频谱感知决策模块 408根据次用户与主用户的冲突概率或 次用户的最大接入能力确定目标信道的感知顺序，感知顺序尽量使单节点平均 吞吐量最大化， 或系统平均吞吐量最大化。
又进一步， 在在节点 400中还包括修正模块 410, 修正模块 410计算通过预 测获得感知结果的目标信道的熵， 用熵来表示该信道的不确定程度，再根据低 不确定性准则对所述其他目标信道的感知结果进行修正。
本发明实施例， 只需要对部分信道进行频谱感知， 减少了感知期的时间， 利用信道间的相关性预测获得其他未感知新到的感知结果，这样降低了频谱感 知的开销，提高了系统的吞吐量。 同时利用信道间的相关性来确定需要感知的 目标信道的顺序及策略，根据感知的结果预测其他目标信道活动感知结果，提 高了系统的准确性， 能够进一步满足感知精度要求的条件下， 减少感知时间提 高吞吐量。
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可 以通过程序指令相关的硬件来完成，前述的程序可以存储于一计算机可读取存 储介质中， 该程序在执行时， 执行包括上述方法实施例的步骤； 而前述的存储 介质包括： ROM、 RAM, 磁碟或者光盘等各种可以存储程序代码的介质。

Claims

权 利 要 求
1、 一种频-潜感知方法， 其特征在于， 包括：
获得目标信道间的相关性信息；
获得至少一条所述目标信道的频谱感知结果；
根据所述至少一条目标信道的频谱感知结果及所述目标信道间的相关性 信息确定其他目标信道的感知结果。
2、 根据权利要求 1所述的方法， 其特征在于， 所述目标信道间的相关性信 息表征信道间频语使用情况的相似程度。
3、 根据权利要求 1所述的方法， 其特征在于， 获得至少一条所述目标信道 的频谱感知结果包括：
直接对所述目标信道中的至少一条目标信道进行频谱感知； 或
接收感知节点发送的所述至少一条目标信道频谱感知结果，其中由所述感 知节点对所述至少一条目标信道进行频谱感知。
4、 根据权利要求 3所述的方法， 其特征在于， 对所述目标信道中的至少一 条目标信道进行频谱感知包括；
根据所述目标信道间的相关性信息在所述目标信道中选择至少一条目标 信道进行频谱感知， 并确定对所述选择出的目标信道的感知顺序，按所述感知 顺序对所述选择出的目标信道进行感知。
5、 根据权利要求 2所述的方法， 其特征在于， 所述目标信道间的相关性信 息包括：
两个信道上主用户出现次数和出现时间的概率； 或
两个信道上业务相似度； 或 两个信道上的信干噪比的相似度。
6、 根据权利要求 1所述的方法， 其特征在于， 所述获得目标信道间的相关 性信息包括：
根据其他频谱测量节点发送的频谱测量结果计算获得所述目标信道间的 相关性信息； 或
根据静态历史频谱测量统计信息计算获得所述目标信道间的相关性信息。
7、 根据权利要求 1所述的方法， 其特征在于， 所述方法还包括： 计算所述其他目标信道的熵， 用所述熵表示该信道的不确定程度； 根据低不确定性准则对所述其他目标信道的感知结果进行修正。
8、 根据权利要求 3所述的方法， 其特征在于， 所述确定对所述选择出的目 标信道的感知顺序包括：
根据次用户与主用户的冲突概率或次用户的最大接入能力确定所述目标 信道的感知顺序， 所述感知顺序使单节点平均吞吐量最大化， 或系统平均吞吐 量最大化。
9、 根据权利要求 1所述的方法， 其特征在于， 所述根据所述至少一条目标 信道的频谱感知结果及所述目标信道间的相关性信息确定其他目标信道的感 知结果包括：
当所述其他信道与所述至少一条目标信道的相似性大于一阈值时，确定所 述其他目标信道的感知结果与所述至少一条目标信道的感知结果相同。
10、 一种频 -潜感知系统节点， 其特征在于， 该节点包括：
测量融合模块， 用于获得目标信道间的相关性信息；
谱感知模块， 用于获得至少一条所述目标信道的频谱感知结果； 测量分析模块，用于根据所述至少一条目标信道的频谱感知结果及所述目 标信道间的相关性信息确定其他目标信道的感知结果。
11、 根据权利要求 10所述的节点， 其特征在于， 所述测量融合模块获得的 目标信道间的相关性信息表征信道间频语使用情况的相似程度。
12、 根据权利要求 10所述的节点， 其特征在于， 所述语感知模块获得至少 一条所述目标信道的频谱感知结果包括：
所述谱感知模块直接对所述目标信道中的至少一条目标信道进行频谱感 知； 或接收其他感知节点发送的所述至少一条目标信道频谱感知结果， 其中由 所述其他感知节点对目标信道进行频谱感知。
13、根据权利要求 12所述的节点，其特征在于，还包括频谱感知决策模块， 用于根据所述目标信道间的相关性信息在所述目标信道中选择至少一条目标 信道进行频谱感知， 并确定对所述选择出的目标信道的感知顺序， 所述语感知 模块或所述其他节点按所述感知顺序对所述选择出的目标信道进行感知。
14、 根据权利要求 13所述的节点， 其特征在于， 所述频谱感知决策模块根 据次用户与主用户的冲突概率或次用户的最大接入能力确定所述目标信道的 感知顺序， 所述感知顺序使单节点平均吞吐量最大化， 或系统平均吞吐量最大 化。
15、 根据权利要求 10所述的节点， 其特征在于， 所述节点还包括： 修正模块， 用于计算所述其他目标信道的熵， 用所述熵表示该信道的不确 定程度； 根据低不确定性准则对所述其他目标信道的感知结果进行修正。
16、 根据权利要求 10所述的节点， 其特征在于， 所述测量分析模块在当所 述其他信道与所述至少一条目标信道的相似性大于一阈值时，确定所述其他目 标信道的感知结果与所述至少一条目标信道的感知结果相同。
17、 一种频谱感知系统， 其特征在于， 所述系统包括：
测量融合节点， 用于获得目标信道间的相关性；
感知节点， 用于从所述测量融合节点获得目标信道间的相关性信息，对至 少一条目标信道进行信道感知， 并根据感知结果和信道的相关性信息，预测其 它未感知信道的状态， 确定其他目标信道的感知结果。
18、 根据权利要求 17所述的系统， 其特征在于， 所述测量融合节点根据所 述目标信道间的相关性信息选择出所述感知节点进行感知的目标信道，并确定 感知顺序。
19、 根据权利要求 17所述的系统， 其特征在于， 所述感知节点从所述测量 融合节点获得目标信道间的相关性信息后根据所述目标信道间的相关性信息 选择出进行感知的目标信道， 并确定感知顺序。
20、 根据权利要求 18或 19所述的系统， 其特征在于， 所述测量融合节点或 者感知节点根据次用户与主用户的冲突概率或次用户的最大接入能力确定所 述目标信道的感知顺序， 所述感知顺序使单节点平均吞吐量最大化， 或系统平 均吞吐量最大化。
21、 根据权利要求 17所述的系统， 其特征在于， 感知节点计算所述其他目 标信道的熵， 根据低不确定性准则对所述其他目标信道的感知结果进行修正， 其中所述熵表示该信道的不确定程度.
22、 根据权利要求 17所述的系统， 其特征在于， 所述节点在当所述其他信 道与所述至少一条目标信道的相似性大于一阈值时，确定所述其他目标信道的 感知结果与所述至少一条目标信道的感知结果相同。
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